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I Never Thought Stroke Would Happen to Me
by Myra Wilson, Stroke Survivor On November 3, 2014, I was in nursing school working as a student nurse at a hospital in Seattle. My first sign that something was not quite right was when I was walking through the nursing station and both of my eyes went blurry. I could still see color but I couldn't see letters. It was blurry for about 30 seconds before clearing up again. I was going to lunch and went to give a report to another nurse. The nurse noticed while I was speaking that I slurred my speech. I didn't notice my speech was slurred at all. It was at that time that I experienced a sudden sharp pain on the right s...
Source: Healthy Living - The Huffington Post - May 13, 2016 Category: Consumer Health News Source Type: news

Cerebral Venous Thrombosis Mimicking Acute Ischemic Stroke in the Emergency Assessment of Thrombolysis Eligibility: Learning from a Misdiagnosed Case
CONCLUSION: Patients with CVT have a higher risk of thrombolysis-related intracranial hemorrhage than other stroke mimics. A greater focus on noncontrast brain CT and the venous phase of CT angiography help identifying this stroke mimic before thrombolysis.PMID:34841501
Source: Acta Neurologica Taiwanica - November 29, 2021 Category: Neurology Authors: Po-Yu Lin Ying-Chen Chen Yuan-Ting Sun Source Type: research

Machine learning and acute stroke imaging
Conclusions ML in acute ischemic stroke imaging has already made tremendous headway. Additional applications and further integration with clinical care is inevitable. Thus, facility with these approaches is critical for the neurointerventional clinician.
Source: Journal of NeuroInterventional Surgery - January 11, 2023 Category: Neurosurgery Authors: Sheth, S. A., Giancardo, L., Colasurdo, M., Srinivasan, V. M., Niktabe, A., Kan, P. Tags: Neuroimaging Source Type: research

Ctbrain machine learning predicts stroke thrombolysis result
Conclusions This proof-of-concept study shows that machine learning methods applied to acute stroke CT-scans potentially offers automation, and improved performance in SICH prediction following thrombolysis. Larger-scale cohorts, and incorporation of CT perfusion/angiography data, should be tested with such methods.
Source: Journal of Neurology, Neurosurgery and Psychiatry - September 9, 2014 Category: Neurosurgery Authors: Epton, S., Bentley, P., Ganesalingam, J., Dias, A., Mahady, K., Rinne, P., Sharma, P., Halse, O., Mehta, A., Rueckert, D. Tags: Abstracts Source Type: research

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